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Digital Labour in the Platform Economy: the Case of Facebook Article Digital Labour in the Platform Economy: The Case of Facebook Andrea Fumagalli 1, Stefano Lucarelli 2,3, Elena Musolino 2,* and Giulia Rocchi 4 1 Department of Economics and Management, Università di Pavia, Pavia 27100, Italy; [email protected] 2 Department of Management, Economics and Quantitative Methods, Università di Bergamo, Bergamo 24127, Italy; [email protected] 3 Centre d'Économie de la Sorbonne at CNRS, Unit of Research 8174, Paris 75013, France 4 Axe Économie Politique, Université Paris 1 Panthéon-Sorbonne, Paris 75013, France; [email protected] * Correspondence: [email protected]; Tel: +39 338 68 61 583 Received: 04 March 2018; Accepted: 23 May 2018; Published: 27 May 2018 Abstract: The aim of the paper is to analyse the features of the digital labour connected with the so-called platform economy. Many platform-based business models rely on a new composition of capital capable of capturing personal information and transforming it into big data. Starting with the example of the Facebook business model, we explain the valorisation process at the core of platform capitalism, stressing the relevance of digital labour, to clarify the crucial distinction between labour and work. Our analysis differs from Fuchs and Sevignani’s thesis about digital work and digital labour and seems consistent with the idea that Facebook extracts a rent from the information produced by the free labour of its users. Keywords: organization of digital labour; platform economy; valorisation process 1. Introduction Notwithstanding the Internet bubble bursting during the late 1990s, the diffusion of information and communication technologies (ICT) continues to mark the 2000s. Particularly in recent years, we have witnessed a significant technological acceleration. Several sectors have been affected. These are industries that have more and more to do with the management of human life (for instance, the Human Genome Project, started in 1990 and concluded in 2003, opened enormous spaces in the possibility of the manipulation of individual life and its procreation [1]). As stressed by Robert Boyer “this sort of regime is an extension of the continued reassessment which has gone on concerning the potential of the information economy” [2]. If the ICT technological paradigm has hit employment levels in the manufacturing industry hard, the new bio-technological wave risks having even greater effects on the traditional and advanced tertiary sectors, which in the last decades have played a compensative role against the loss of jobs in traditional industries. The development of second generation algorithms [3] is allowing an automation process unprecedented in human history. Applied to machine tools, through computer technologies and nanotechnologies, they are able to transform them into increasingly flexible and ductile instruments and means of production. Second generation algorithms differ from the first generation due to their cumulative self-learning nature, hence configuring a new relationship between human and machine. Actually, after the first stage of implementation and creation, thanks to human behaviour, they are then able to operate in an almost total condition of automation (machine learning). The current technologies however, cannot operate without the acceleration (compared to the recent past) of the degree of collection and manipulation of extremely large amount of data in more and Sustainability 2018, 10, 1757; doi:10.3390/su10061757 www.mdpi.com/journal/sustainability Sustainability 2018, 10, 1757 2 of 16 more narrow spaces and with ever-increasing high speed. Already in 2011, research by McKinsey’s Global Institute examined the state of digital data and recognized the significant value that can potentially be unlocked: “There are five broad ways in which using big data can create value. First, big data can unlock significant value by making information transparent and usable at much higher frequency. Second, as organizations create and store more transactional data in digital form, they can collect more accurate and detailed performance information on everything from product inventories to sick days, and therefore expose variability and boost performance. Leading companies are using data collection and analysis to conduct controlled experiments to make better management decisions; others are using data for basic low-frequency forecasting to high-frequency now casting to adjust their business levers just in time. Third, big data allows ever-narrower segmentation of customers and therefore much more precisely tailored products or services. Fourth, sophisticated analytics can substantially improve decision-making. Finally, big data can be used to improve the development of the next generation of products and services.” [4] As argued by Martin Kenney and John Zysman, among others, “the algorithmic revolution and cloud computing are the foundations of the platform economy. But computing power is only the beginning of the story. That computing power is converted into economic tools using algorithms operating on the raw material of data.” [5] In the emerging digital platform economy, data as the final output, which is then realized on the global communication and advertising markets, originates a “network value” as the result of a continuous and dynamic process of interaction between human and linguistic labour and digitalized infrastructures (the platforms) [6]. A necessary (although not sufficient) condition for an algorithm to be exploited at maximum power is the existence of a standardization process of cataloguing the necessary data in relation to the predetermined purpose. This is made possible by the manipulation techniques for so-called “big data”, especially the big data analytical/mining techniques for structured and unstructured data (commonly called “data extraction”), as well explained in the literature on technology management by Amir Gandomi and Murtaza Haider [7]. Big data represent not only some of the most granular data ever existing generated second-by- second by every device and part of software connected to the web, but also represent an instrument able to change the deep meaning of human activities and particularly human labour. In Platform Capitalism, Nick Srnicek provides one of the first systemic Marxist interventions into the discourse around data-driven digitalization and the future of work [8]. According to Srnicek, the evolution of internet technologies has fundamentally altered the scenery of capital accumulation and property relations between firms, and legitimates the following question: does the emergence of platform capitalism constitute a new mode of exploitation? Srnicek offers an innovative framework through which to address this question in his conception of data as ‘raw material,’ but his analysis is limited to the effects of lean platforms on the labour market. From a Marxian perspective, two other problems should be considered: of what does the transformation process of personal information into big data consist? And, moreover, what is the origin of value in the platform economy? Starting with the example of the Facebook case, we explain the valorisation process at the core of platform capitalism, stressing the relevance of digital labour as a source of economic value for an ever increasing number of data-fuelled corporations. The main aim of Section 2 is the presentation of the value creation model used by Facebook. Indeed, the American online social media and social networking service company launched by Mark Zuckerberg represents an example of an advertising platform in which value is essentially based on a process of expropriation of the life skills of individuals. In the traditional way, platform capitalism has mainly to do with the satisfaction of some consumer services and the management of the sectors related to the logistics management of commodities. The most affected industries concern the tertiary sector, even if some aspects of the manufacturing sectors are involved. This Sustainability 2018, 10, 1757 3 of 16 perspective seems common to Nick Srnicek’s argument and the McKinsey reports on big data. This analysis of platform capitalism does not consider other relevant features of the economic model, especially the fact that the human activities on Internet platforms are increasingly integrated with the digital elements of communication and language, as we argue in Section 3. It is then necessary to elucidate the crucial distinction between labour and work in order to propose a specific definition of “digital labour”, as we do in Section 4 after discussing the concept within the Marxian debate. We particularly refer to the recent contributions by Christian Fuchs and Sebastian Sevignani (2013) [9] and Trebor Scholz (2017) [10]. Section 5 concludes. 2. The Case of Facebook As shown in Figure 1, Facebook is the undisputed global leader in the social network domain. Figure 1. World map of social networks. Source: http://vincos.it/world-map-of-social-networks. As of the first quarter of 2017, the worldwide number of Facebook monthly active users amounted to 1.94 billion, with an increase of 17% year-over-year [11]. A monthly active user (MAU) is defined as a registered Facebook user who logged in and visited Facebook through the website or a mobile device, or used the Messenger application at least one time in the last 30 days; this metric, as well as those about the daily active users (DAUs) and the average revenue per user (ARPU), do not include Instagram,
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